Most existing particle swarm optimization (PSO) variants use a single learning strategy and a fixed neighborhood structure for all particles during the search process. The adoption of rigid learning pattern and communication topology may restrict the intelligence level of each particle, hence degrading the performance of PSO in solving the optimization problems with complicated fitness landscapes. Recent studies suggested that the employment of self-adaptive mechanism in adjusting the search strategy and topology connectivity of each particle along the search process may serve as a potential remedy to improve the performance of PSO, especially when dealing with complex problems. For this reason, a self-adaptive topologically connected (SATC)-based PSO equipped with an SATC module and an improved learning framework is proposed. The SATC module is envisioned to facilitate each particle to perform searching with different exploration and exploitation strengths by adaptively modifying its topology connectivity in different searching stages. A modified velocity update scheme and an alternative search operator are also introduced to formulate an improved learning framework to enhance the performance of proposed work further. Substantial numbers of benchmark functions and two real-world optimization problems are used to compare SATC-based PSO (SATCPSO) with several well-established PSO variants. Extensive studies have verified that SATCPSO is more competitive than its peers in most of the tested problems.

Tracking the speed and current in permanent magnet synchronous motors (PMSMs) for industrial applications is challenging due to various external and internal disturbances such as parameter variations, unmodelled dynamics, and external load disturbances. Inaccurate tracking of speed and current results in severe system deterioration and overheating. Therefore, the design of the controller for a PMSM is essential to ensure the system can operate efficiently under conditions of parametric uncertainties and significant variations. The present work proposes a PMSM speed controller using machine learning (ML) techniques for quick response and insensitivity to parameter changes and disturbances. The proposed ML controller is designed by learning fractional-order sliding mode control (FOSMC) controller behavior. The primary purpose of using ML in FOSMC is to avoid the self-tuning of the parameters and ensure the speed reaches the reference value in finite time with faster convergence and better tracking precision. Furthermore, the ML model does not require the mathematical model of the speed controller. In this work, several ML models are empirically evaluated on their estimation accuracy for speed tracking, namely ordinary least squares, passive-aggressive regression, random forest, and support vector machine. Finally, the proposed controller is implemented on a real-time hardware-in-the-loop (HIL) simulation platform from PLECS Inc. Comparative simulation and experimental results are presented and discussed. It is shown from the comparative study that the proposed FOSMC based on ML outperformed the traditional sliding mode control (SMC), which is more commonly used in industry in terms of tracking speed and accuracy.

Technology is advancing with the times. Augmented reality (AR) received great attention in education because it focuses on technology that connects the real and virtual worlds in real-time. The blending of AR technology and educational content aims to generate innovative thinking that can improve the effectiveness of teaching and learning for students in real-life scenarios. This study aimed to develop an AR module and application (apps.) for high school students to learn about food technology. Five phases of the analysis, design, development, implementation, and evaluation (ADDIE) model were used to develop food technology applications in the classroom based on AR technology. An interview was conducted to obtain the usability of the AR module from the selected expert. The results showed that iFoodAR fulfilled the requirement in line with the standard curriculum and assessment document (DSKP) of the Malaysian Ministry of Education and gained positive feedback on using AR in the classroom from the expert teachers. It is concluded that iFoodAR apps have the potential to cater the diversity learning styles, leading to a shift in teaching methods incorporating more interactive and visually stimulating learning experiences.

Studies have indicated that the COVID-19 pandemic has had miserable effects on athlete performance due to the movement control order (MCO) announced by the Malaysia Government. Dealing with self-training without the coach's guidance leads the archers to lose concentration, diminished self-confidence, and elevated anxiety levels. These factors contribute to inconsistent shooting performance. This study attempted to identify the archer's anxiety status during the training isolation period on the shooting performance. A total of 32 participants from the recurve archery category were recruited and enrolled in a web-based cross-sectional study during the MCO. The CSAI-2R instrument was applied to participants to examine the psychological aspect. Training Isolation resulted in a significant effect on anxiety status and shooting performance. Analysis from CSAI-2R, low-level archers, indicated 5% more anxiety than top-level archers for both cognitive and somatic anxiety sub-component. In contrast, Top archers revealed a higher self-confidence mean of 2.32 (moderately high) than low archers (1.38). The result shows improvement in anxiety and score performance with complete online monitoring and coaching supervision first session until the 8th session. These findings could assist sports institutions in improving a better training experience and understanding the pandemic's impact on athletes' mental health during home isolation.

The water crisis is identified as the most serious global risk for the coming decade. Distilled water is one of the on-demand elements in academic laboratories; however, water scarcity may eventually affect the education sector, necessitating the implementation of new policies. Human behavior, awareness, knowledge, and opinion is having an impact on water management; accordingly, a questionnaire was purposely designed and validated to assess these variables in a Malaysian public university regarding the use of non-distilled water produced by the distillation process. An exploratory factor analysis yielded four factors: “concept of green laboratory and water”, “usage of non-distilled water”, “knowledge about water distillation”, and “behavior related to water conservation”. Using the Mann–Whitney U test to compare laboratory and non-laboratory users’ responses, the variables “Knowledge”, “Behavior”, and “Opinion” revealed statistically significant differences, with laboratory users scoring higher in all four variables. Employing the Kruskal–Wallis H test in an occupation-based comparison among laboratory users, and with an additional variable “Practice”, showed that “Lecturer” has the highest mean rank for “Awareness”, “Behavior”, and “Opinion”, while “Laboratory Assistant” has the highest mean rank for “Knowledge”. This study provides a rationale analysis for future insights to educate faculty members about the reuse of non-distilled water sustainably.

The incorporation of technology is a consistent aspect of education, which is widely advanced through teaching and learning (T&L) in the industrial revolution 4.0 (IR 4.0) education technology. In this study, an automatic thread insertion set for sewing (ATIKs) was developed. The ATIKs device improves students' understanding and facilitates the process of sewing in fashion design subjects for high school curriculum. The device was programmed using an Arduino microcontroller board and open source Arduino software (IDE). The CDIO model is used as the basis for product development, which includes the steps from conception to design, implementation, and operation. The development for this product consists of the main components standard needle size, automatic thread, Arduino UNO R3, stepper motor, coil, and Arduino coding to control the movement. In addition, this product is relatively portable with its dimensions of 7 x 7 x 10 cm. A qualitative research method was applied using a list of interview protocols validated by five professional experts in the field. Based on the open-ended questions, the experts indicated that this product facilitates the criteria of the T&L process, improves understanding of the use of the thread needle, and increases student confidence in the sewing process. In the future, this kit could be integrated into an automated control system. This research development can help develop teaching tools that further increase student safety and improve student skills and cleanliness in handling sewing tools during hands-on work.